Informatics in Education

This article examines pre-service teachers’ data agency, defined as the ability to act according to one’s own values and goals rather than being directed by algorithmic systems. Data agency involves understanding how computational systems, such as algorithms, data-driven profiling, and platform infrastructures, collect, process, and use data, and how these practices shape individuals and society. This article introduces a self-assessment instrument developed to measure data agency and applies it to a sample of 163 Finnish pre-service teachers. The findings show that pre-service teachers evaluated their competencies across different dimensions of data agency rather cautiously. The study highlights the importance of strengthening future teachers’ understanding of the mechanisms behind algorithmic and data-driven decision-making. Such knowledge is increasingly essential for preparing future teachers to address challenges related to datafication, including commercial data collection and algorithmic influencing in contemporary education.

In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life and developing agency in a digital world. This paper presents a qualitative study that explores students’ perspectives on the relevance of learning concepts of data-driven technologies for navigating the digital world. The underlying approach of the study is data awareness, which aims to support students in understanding and reflecting on such technologies to develop agency in a data-driven world. This approach teaches students an explanatory model encompassing several concepts of the role of data in data-driven technologies. We developed an intervention and conducted retrospective interviews with students. Findings from the analysis of the interviews indicate that students can analyse and understand data-driven technologies from their everyday lives according to the central role of data. In addition, students’ answers revealed four areas of how learning about data-driven technologies becomes relevant to them. The paper concludes with a preliminary model suggesting how computing education can make concepts of data-driven technologies meaningful for students to understand and navigate the digital world.